The squeeze cell hypothesis for the activation of jasmonate synthesis in response to wounding

Jasmonates are lipid mediators that control defence gene expression in response to wounding and other environmental stresses. These small molecules can accumulate at distances up to several cm from sites of damage and this is likely to involve cell-to-cell jasmonate transport. Also, and independently of jasmonate synthesis, transport and perception, different long-distance wound signals that stimulate distal jasmonate synthesis are propagated at apparent speeds of several cmmin(-1) to tissues distal to wounds in a mechanism that involves clade 3 GLUTAMATE RECEPTOR-LIKE (GLR) genes. A search for jasmonate synthesis enzymes that might decode these signals revealed LOX6, a lipoxygenase that is necessary for much of the rapid accumulation of jasmonic acid at sites distal to wounds. Intriguingly, the LOX6 promoter is expressed in a distinct niche of cells that are adjacent to mature xylem vessels, a location that would make these contact cells sensitive to the release of xylem water column tension upon wounding. We propose a model in which rapid axial changes in xylem hydrostatic pressure caused by wounding travel through the vasculature and lead to slower, radially dispersed pressure changes that act in a clade 3 GLR-dependent mechanism to promote distal jasmonate synthesis.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Synthesis of chemically functionalized superparamagnetic nanoparticles as delivery vectors for chemotherapeutic drugs.

Superparamagnetic iron oxide nanoparticles (SPIONs) are in clinical use for disease detection by MRI. A major advancement would be to link therapeutic drugs to SPIONs in order to achieve targeted drug delivery combined with detection. In the present work, we studied the possibility of developing a versatile synthesis protocol to hierarchically construct drug-functionalized-SPIONs as potential anti-cancer agents. Our model biocompatible SPIONs consisted of an iron oxide core (9-10 nm diameter) coated with polyvinylalcohols (PVA/aminoPVA), which can be internalized by cancer cells, depending on the positive charges at their surface. To develop drug-functionalized-aminoPVA-SPIONs as vectors for drug delivery, we first designed and synthesized bifunctional linkers of varied length and chemical composition to which the anti-cancer drugs 5-fluorouridine or doxorubicin were attached as biologically labile esters or peptides, respectively. These functionalized linkers were in turn coupled to aminoPVA by amide linkages before preparing the drug-functionalized-SPIONs that were characterized and evaluated as anti-cancer agents using human melanoma cells in culture. The 5-fluorouridine-SPIONs with an optimized ester linker were taken up by cells and proved to be efficient anti-tumor agents. While the doxorubicin-SPIONs linked with a Gly-Phe-Leu-Gly tetrapeptide were cleaved by lysosomal enzymes, they exhibited poor uptake by human melanoma cells in culture.

Glutamine synthesis rate in the hyperammonaemic rat brain using simultaneous localized in vivo H-1 and N-15 MRS

Objectives: Glutamine synthetase is a critical step in the glutamate-glutamine cycle, the major mechanism of glutamate neurotransmission and is implicated in the mechanism of ammonia toxicity. 15N MRS is an alternative approach to 13C MRS in studying glutamate- glutamine metabolism. 15N MRS studies allow to measure an apparent glutamine synthesis rate (Vsyn) which reflects a combination of the glutamate- glutamine cycle activity (Vnt) and net glutamine accumulation. The net glutamine synthesis (Vsyn-Vnt) can be directly measured from 1H NMR. Therefore, the aim of this study was to perform in vivo localized 1H MRS interleaved with 15N MRS to directly measure the net glutamine synthesis rate and the apparent glutamine synthesis rate under 15N labeled ammonia infusion in the rat brain, respectively. Methods: 1H and 15N MRS data were acquired interleaved on a 9.4T system (Varian/Magnex Scientific) using 5 rats. 15NH4Cl solution was infused continuously into the femoral vein for up to 10 h (4.5 mmol/h/kg).1 The plasma ammonia concentration was increased to 0.95±0.08 mmol/L (Analox GM7 analyzer). 1H spectra were acquired and quantified as described previously.2 15N unlocalized and localized spectra were acquired using the sequence;3 and quantified using AMARES and an external reference method.4 The metabolic model used to analyze the total Gln and 5-15N labeled Gln time courses is shown on Figure 1A. Results: Glutamine concentration increased from 2.5±0.3 to 15±3.3 mmol/kg whereas the total glutamate concentrations remained unchanged (Figure 1B). The linear fit of the time-evolution of the total Gln from the 1H spectra gave the net synthesis flux (Vsyn-Vnt), which was 0.021± 0.006 mmol/min per g (Figure 1D). The 5-15N Gln peak (_271 ppm) was visible in the first and all subsequent scans, whereas the 2-15N Gln/Glu peak (_342 ppm) appeared after B1.5 h (Figure 1C). From the in vivo 5-15N Gln time course, Vsyn = 0.29±0.1 mmol/min per g and a plasma NH3 fractional enrichment of 71%±6% were calculated. Vnt was 0.26±0.1 mmol/min/g, obtained assuming a negligible Gln efflux.5 Vsyn and Vnt were within the range of 13C NMR measurements.6 Conclusion: The combination of 1H and 15N NMR allowed for the first time a direct and localized measurement of Vnt and apparent glutamine synthesis rate. Vnt is approximately one order of magnitude faster than the net glutamine accumulation.

ZHARP: three-dimensional motion tracking from a single image plane.

Three-dimensional imaging and quantification of myocardial function are essential steps in the evaluation of cardiac disease. We propose a tagged magnetic resonance imaging methodology called zHARP that encodes and automatically tracks myocardial displacement in three dimensions. Unlike other motion encoding techniques, zHARP encodes both in-plane and through-plane motion in a single image plane without affecting the acquisition speed. Postprocessing unravels this encoding in order to directly track the 3-D displacement of every point within the image plane throughout an entire image sequence. Experimental results include a phantom validation experiment, which compares zHARP to phase contrast imaging, and an in vivo study of a normal human volunteer. Results demonstrate that the simultaneous extraction of in-plane and through-plane displacements from tagged images is feasible.

Durable, Cost-Effective Pavement Markings Phase I: Synthesis of Current Reseaech, June 2001

Pavement marking technology is a continually evolving subject. There are numerous types of materials used in the field today, including (but not limited to) paint, epoxy, tape, and thermoplastic. Each material has its own set of unique characteristics related to durability, retroreflectivity, installation cost, and life-cycle cost. The Iowa Highway Research Board was interested in investigating the possibility of developing an ongoing program to evaluate the various products used in pavement marking. This potential program would maintain a database of performance and cost information to assist state and local agencies in determining which materials and placement methods are most appropriate for their use. The Center for Transportation Research and Education at Iowa State University has completed Phase I of this research: to identify the current practice and experiences from around the United States to recommend a further course of action for the State of Iowa. There has been a significant amount of research completed in the last several years. Research from Michigan, Pennsylvania, South Dakota, Ohio, and Alaska all had some common findings: white markings are more retroreflective than yellow markings; paint is by-and-large the least expensive material; paint tends to degrade faster than other materials; thermoplastic and tapes had higher retroreflective characteristics. Perhaps the most significant program going on in the area of pavement markings is the National Transportation Product Evaluation Program (NTPEP). This is an ongoing research program jointly conducted by the American Association of State Highway and Transportation Officials and its member states. Field and lab tests on numerous types of pavement marking materials are being conducted at sites representing four climatological areas. These results are published periodically for use by any jurisdiction interested in pavement marking materials performance. At this time, it is recommended that the State of Iowa not embark on a test deck evaluation program. Instead, close attention should be paid to the ongoing evaluations of the NTPEP program. Materials that fare well on the NTPEP test de cks should be considered for further field studies in Iowa.

Erosion Control for Highway Applications, Phase I: Review and Synthesis of Literature, Final Report, TR-464, May 2002

The project described herein has led to a convenient, computer-based expert system for identifying and evaluating potentially effective erosion- and sedimentation-control measures for use in roadway construction throughout Iowa and elsewhere in the Midwest. The expert system is intended to be an accessible and efficient practical resource to aid state, county, and municipal engineers in the selection of the best management practices for preventing unwanted erosion and sedimentation at roadway construction sites, during and after construction.

Effect of olive oil on early and late events of colon carcinogenesis in rats: modulation of arachidonic acid metabolism and local prostaglandin E2 synthesis.

BACKGROUND Animal model studies have shown that the colon tumour promoting effect of dietary fat depends not only on the amount but on its fatty acid composition. With respect to this, the effect of n9 fatty acids, present in olive oil, on colon carcinogenesis has been scarcely investigated. AIMS To assess the effect of an n9 fat diet on precancer events, carcinoma development, and changes in mucosal fatty acid composition and prostaglandin (PG)E2 formation in male Sprague-Dawley rats with azoxymethane induced colon cancer. METHODS Rats were divided into three groups to receive isocaloric diets (5% of the energy as fat) rich in n9, n3, or n6 fat, and were administered azoxymethane subcutaneously once a week for 11 weeks at a dose rate of 7.4 mg/kg body weight. Vehicle treated groups received an equal volume of normal saline. Groups of animals were colectomised at weeks 12 and 19 after the first dose of azoxymethane or saline. Mucosal fatty acids were assessed at 12 and 19 weeks. Aberrant crypt foci and the in vivo intracolonic release of PGE2 were assessed at week 12, and tumour formation at week 19. RESULTS Rats on the n6 diet were found to have colonic aberrant crypt foci and adenocarcinomas more often than those consuming either the n9 or n3 diet. There were no differences between the rats on the n9 and n3 diets. On the other hand, administration of both n9 and n3 diets was associated with a decrease in mucosal arachidonate concentrations as compared with the n6 diet. Carcinogen treatment induced an appreciable increase in PGE2 formation in rats fed the n6 diet, but not in those fed the n3 and n9 diets. CONCLUSIONS Dietary olive oil prevented the development of aberrant crypt foci and colon carcinomas in rats, suggesting that olive oil may have chemopreventive activity against colon carcinogenesis. These effects may be partly due to modulation of arachidonic acid metabolism and local PGE2synthesis.